Originally published on Causal Signal on Substack, April 17, 2024.

Reducing Abandonment and Improving Customer Experience through Effective Wait Time Management

In recent years, Virtual Waiting Rooms have become increasingly prevalent across various industries, from ride-sharing and food delivery to retail and healthcare.

A recent study, titled "Delay Information in Virtual Queues: A Large-Scale Field Experiment on a Ride-Sharing Platform," reveals that both the magnitude of the initial wait time information (WTI) provided to customers and the frequency of subsequent wait time updates significantly impact customer abandonment rates.

By carefully manipulating these factors, businesses can strike a balance between reducing abandonment and ensuring a positive customer experience.

Key Takeaways

  1. Both the magnitude of the initial wait time information (WTI) provided to customers and the frequency of subsequent wait time updates impact customer abandonment behavior in virtual queues.
  2. Providing a slightly pessimistic initial WTI (1 minute longer than the neutral estimate) followed by frequent 1-minute downward updates can improve customer experience without increasing abandonment.
  3. When the initial WTI estimate is 2 or more minutes longer than the neutral estimate, the magnitude effect dominates, increasing abandonment likelihood by 6-20%.
  4. Optimistic initial WTI (2+ minutes shorter than neutral estimate) can reduce abandonment by 10%+ but risks worse customer experience if wait times exceed expectations.Virtual queue managers must weigh this short-term benefit against potential long-term customer retention impact.
  5. If congestion is very high, providing a significantly pessimistic initial wait time estimate (2+ min more than neutral) can be beneficial. It increases abandonment of less patient customers quickly, reducing unnecessary waiting for customers who ultimately won't be served due to capacity limits. This helps both customers and the service provider.
  6. The magnitude effect occurs in the first 30 seconds. A 1-minute change in initial WTI impacts abandonment likelihood by 6.9% in that time. The update-frequency effect occurs later, reducing abandonment likelihood around update times, offsetting the magnitude effect for small differences.
  7. Beyond ride-sharing, these findings likely extend to other services adopting virtual queues, especially post-COVID, such as retail, restaurants, healthcare, delivery, etc. Effective WTI can help balance supply and demand.
The magnitude of initial wait time estimates and the frequency of updates significantly impact customer abandonment in virtual queues. Pessimistic initial estimates (1-4 minutes longer than neutral) can reduce abandonment without hurting experience, while optimistic estimates (2+ minutes shorter) risk disappointment. Frequent 1-minute updates after a pessimistic initial estimate can offset abandonment through a positive update-frequency effect.

Practical Applications

  1. As a default, provide initial WTI estimate 1 minute longer than the neutral estimate. This improves customer experience without increasing abandonment, based on the offsetting magnitude and frequency effects.
  2. For highly supply-constrained situations, consider providing initial WTI estimate 2-4 minutes longer than the neutral estimate. This can increase abandonment by 6-16% for customers who likely won't be served, reducing their unnecessary waiting.
  3. Be cautious with optimistic WTI estimate (2+ minutes less than neutral). While it can reduce abandonment by 10%+, it risks worse customer experience and potential long-term retention and lifetime value impact if wait times exceed expectations. Use selectively.
  4. Recognize that even 1-minute changes in initial WTI estimate have a sizable ~7% impact on abandonment likelihood in the first 30 seconds due to the magnitude effect. Manage this initial WTI estimate carefully.
  5. Provide frequent 1-minute downward updates after a pessimistic initial WTI estimate. The positive update-frequency effect can offset initial pessimism, reducing abandonment likelihood at update times.
  6. Experimenting with WTI ranges rather than point estimates, varying width and midpoint skew to optimize for specific contexts.
  7. When adopting virtual queues, use these WTI insights as part of a comprehensive approach to improve customer experience and operational efficiency. Adapt the specific tactics (e.g. 1 vs. 2+ minute WTI differences) based on industry and context.
  8. Consider advanced WTI approaches that leverage customer-specific data, such as prior wait time experiences, to provide more personalized estimates and ranges that further optimize abandonment and customer experience.
To optimize virtual queues, provide initial wait time estimates 1 minute longer than neutral, and 2-4 minutes longer in highly constrained situations. Experiment with wait time ranges, and provide frequent 1-minute updates, especially after pessimistic initial estimates.

Conclusion

As virtual queues aka virtual waiting rooms continue to gain prominence across various industries, it is imperative for businesses to adopt a data-driven approach to wait time management.The insights in the paper can provide a foundation for developing comprehensive strategies that leverage WTI updates to enhance customer experiences and operational efficiency.

By strategically leveraging the magnitude and frequency of wait time updates, companies can effectively optimize customer behavior, reduce abandonment rates, and enhance overall satisfaction. The findings underscore the importance of striking a delicate balance between setting realistic expectations and providing a positive waiting experience.

Learn how you can implement intelligent queues that offer real-time updates and personalized experiences with PhotonIQ Virtual Waiting Rooms. Experience a walkthrough demo to see a variety of use cases, or chat with an expert.

Elevate the waiting experience, turning idle time into an opportunity for engagement and satisfaction.

Photo by Unsplash+In collaboration with Getty Images.